Medical Diagnosis in Chest X-ray images.

An Image-Classifier made using pre-trained network/model 'densenet121' having an accuracy of 98%.

Employing Error Level Analysis (ELA) and Edge Detection techniques, this project aims to identify potential image forgery by analyzing discrepancies in error levels and abrupt intensity changes within images.

Medical Images processing

Optimization of CheXNet in PyTorch with Intel OpenVINO

Followed a paper published on NIH. Replicated the same process and got similar results.

🚀DenseNet Model by Pytorch

6-class image classification using simple CNN, ResNet50, VGG16 and DenseNet121. Dataset contains 2,527 images (glass, paper, cardboard, plastic, metal, trash)

An Image Classification project w/ MobileNetV2 and DenseNet-121. Leveraging techniques like Hyperparameter Tuning, Transfer Learning, Imagine Preprocessing Techniques and Ensemble Methods.

Breast Cancer H&E classification of Images and Image Generation

Hello visitor,

cifar 10 dataset and minist dataset

The main concentration of this project lies on image calssification using traditional CNN(Convolution Neural Networks), and also a couple of "BASE MODELS" such as "RestNet50", "DenseNet121" and "EfficientNetB0" that upgraded the performance of our CNN, followed by the Fully Connected NN, that we are using to train our model on.

The code in this repository was a part of a Bachelor thesis project at KTH.

Custom DenseNet for deepfake detection

Various codes and scripts used during AI research, all neatly organised

A painting classifier made of DenseNet121 using FastAI api. This model can classify 10 types of paintings.

Messing around with object detection from scratch